Abstract: Methods, systems, and computer program products for anomaly and mode inference from time series data are provided herein. A computer-implemented method includes receiving time-series sensor data for each one of a group of devices; extracting a set of states for each device in the group from the time-series sensor data; constructing a state-transition graph for each of the devices, wherein each of the state-transition graphs comprises nodes corresponding to each state in the set and edges corresponding to a probability of transition between the extracted states over time; identifying, for each set, a given state as one of: a mode, a normal state and an anomalous state based on the state-transition graph; and detecting one or more anomalous devices in the group by computing similarities between different devices in the group, based at least in part on the determined state-transition graphs.

Abstract: One embodiment provides a method, including: obtaining, at an information handling device, an image of a person; determining physical characteristics of the person by analyzing the image; receiving an image of at least one selected piece of jewelry, the selected jewelry having a given jewelry profile, wherein the jewelry profile describes features and construction of the selected piece of jewelry; overlaying the image of the at least one selected piece of jewelry onto an image of the person, wherein the overlaying comprises analyzing resizing the image of the at least one selected piece of jewelry to match the physical characteristics of the person, in view of the jewelry profile of the at least one selected piece of jewelry; and providing, on a display of the information handling device, an output image of the image of the person comprising the overlaid image of the at least one piece of jewelry.

Abstract: Methods, systems and computer program products for resource position planning are provided herein. A computer-implemented method includes generating a multi-commodity flow network for locations of a distributed service network over a planning horizon. The method also includes obtaining a set of candidate outage scenarios for the distributed service network, each of the set of candidate outage scenarios being associated with a corresponding probability of occurrence. The method also includes generating a resource positioning configuration for resources in the multi-commodity flow network utilizing an optimization model that reduces unmet demand for each of the set of candidate outage scenarios based at least in part on the probability of occurrence of each of the set of candidate outage scenarios.

Abstract: Methods, systems, and computer program products for demand sensing for product and design introductions are provided herein. A computer-implemented method includes receiving a query comprising information pertaining to an enterprise offering; determining a given number of similar past enterprise offerings based on a comparison of the enterprise offering against a collection of past enterprise offerings and user reviews of the past enterprise offerings; extracting multiple features from the given number of similar past enterprise offerings; generating, for each of the extracted features, a feature-based demand score based on analysis of the user reviews of the given number of similar past enterprise offerings; determining demand for the enterprise offering by aggregating the feature-based demand scores with similarity scores attributed to the enterprise offering with respect to the given number of similar past enterprise offerings; and outputting the demand for the enterprise offering to an enterprise user.

Abstract: A neural network based search system is provided. A first digital image is analyzed by a user device. A targeted object in the first digital image is determined based, at least in part, on (i) the characteristics of the first digital image and (ii) the features of the targeted object. A vector array is generated based, at least in part, on (i) the first digital image and (ii) the targeted object. The vector array is analyzed by the user device. The targeted object is determined based, at least in part, by the vector array. A plurality of digital images is identified based, at least in part, on the similarity of the plurality of digital images and (i) the first digital image and (ii) the targeted object responsive to identifying a plurality of digital images, a query processing is generated. The query map is generated on a user device.

Abstract: A method, system, and computer program product to manage a network comprising a plurality of interconnected components are described. The method includes obtaining a set of all the components that are part of the network over time, and identifying one or more repeating patterns of components among the set of all the components as corresponding lower-level definitions to generate a hierarchical set of all the components. The method also includes obtaining time-varying information regarding topology and operational values within the network, and creating a representation of the network at a set of times based on the hierarchical set of all the components and the time-varying information.

Abstract: A system and method perform calibration of a forecast model for resource allocation. The method includes receiving inputs to the forecast model derived from historical data for a period of time, and executing the forecast model to obtain one or more forecast levels for each interval within the period of time, the forecast level corresponding with a quantified forecast of a forecast parameter that is forecast by the forecast model for the interval. Obtaining an actual level for each interval within the period of time according to the historical data is followed by comparing the one or more forecast levels with the actual level for the period of time according to a metric to adjust a mapping within the forecast model between values of the quantified forecast and the forecast levels based on the comparing to obtain a calibrated forecast model. The calibrated forecast model is used for resource allocation.

Abstract: A method, system, and computer program product for resource management are described. The method includes selecting trouble regions within the service area, generating clustered regions, and training a trouble forecast model for the trouble regions for each type of damage, the training for each trouble region using training data from every trouble region within the clustered region associated with the trouble region. The method also includes applying the trouble forecast model for each trouble region within the service area for each type of damage, determining a trouble forecast for the service area for each type of damage based on the trouble forecast for each of the trouble regions within the service area, and determining a job forecast for the service area based on the trouble forecast for the service area, wherein the managing resources is based on the job forecast for the service area.

Abstract: A method, system, and computer program product to manage a network comprising a plurality of interconnected components are described. The method includes obtaining a set of all the components that are part of the network over time, and identifying one or more repeating patterns of components among the set of all the components as corresponding lower-level definitions to generate a hierarchical set of all the components. The method also includes obtaining time-varying information regarding topology and operational values within the network, and creating a representation of the network at a set of times based on the hierarchical set of all the components and the time-varying information.

Abstract: A method of presenting data over a Web service interface includes: establishing, by a first computer process, a persistent transmission control protocol (TCP) network connection between the first computer process and a second computer process; dynamically allocating, by the second computer process, memory in response to receipt of static data over the persistent TCP network connection from the first computer process; updating, by the second computer process, the memory in response to receipt of dynamic data received over the persistent TCP network connection from the first computer process; and enabling, by the second computer process, a Web server to access the updated data for presentation by the Web service interface. The static data identifies a given entity and the dynamic data includes metric data provided for the entity.

Abstract: Methods, systems and computer program products for resource demand prediction are provided herein. A computer-implemented method includes obtaining historical data logs for activities performed in a distributed service network, the distributed service network comprising a plurality of locations. The method also includes identifying factors influencing resource demand for the distributed service network, determining one or more constraints for specifying activity sequence ordering for activities performed in the distributed service network and generating a statistical model of the distributed service network utilizing the historical data logs, the identified factors and the determined constraints.

Abstract: A method, system, and computer program product for resource management are described. The method includes selecting trouble regions within the service area, generating clustered regions, and training a trouble forecast model for the trouble regions for each type of damage, the training for each trouble region using training data from every trouble region within the clustered region associated with the trouble region. The method also includes applying the trouble forecast model for each trouble region within the service area for each type of damage, determining a trouble forecast for the service area for each type of damage based on the trouble forecast for each of the trouble regions within the service area, and determining a job forecast for the service area based on the trouble forecast for the service area, wherein the managing resources is based on the job forecast for the service area.

Abstract: Methods, systems and computer program products for resource position planning are provided herein. A computer-implemented method includes generating a multi-commodity flow network for locations of a distributed service network over a planning horizon. The method also includes obtaining a set of candidate outage scenarios for the distributed service network, each of the set of candidate outage scenarios being associated with a corresponding probability of occurrence. The method also includes generating a resource positioning configuration for resources in the multi-commodity flow network utilizing an optimization model that reduces unmet demand for each of the set of candidate outage scenarios based at least in part on the probability of occurrence of each of the set of candidate outage scenarios.

Abstract: Embodiments of the present invention disclose a method, a computer program product, and a computer system for predictive maintenance of refrigeration cases. A computer collects a temperature time series for a refrigeration case and, based on the temperature time series, learns a refrigeration case signature for both non-frost and defrost cycles. The computer generates features based on the refrigeration case signature and compares the refrigeration case signature to real time, or observed, temperatures and features using a rule-based and/or machine learning framework. Based on determining that the real time data varies beyond a threshold from the refrigeration case signature, the computer identifies a failure symptom of the refrigeration case and diagnoses a root cause of the symptom or failure. In addition, the computer may activate an alarm and open a work order corresponding to the root cause of the symptom or failure.

Abstract: The present invention provides a method, system, and computer program product of modeling and calculating aggregate power of a set of renewable energy source stations using power output from representative renewable energy source stations. In an embodiment, the present invention includes receiving location, power output time series, and weather time series data of renewable energy source stations in a geographic region and aggregate power output time series data for the geographic region, for each cluster of stations, normalizing the aggregate power value to a representative renewable energy source station, learning a regression model, and de-normalizing a normalized aggregate output power model with respect to a maximum possible power value, and applying a combined model to the received data and power output of representative renewable energy source stations for a particular day, resulting in a total aggregate power value of the renewable energy source stations for the particular day.

Abstract: Embodiments of the present invention disclose a method, a computer program product, and a computer system for predictive maintenance of refrigeration cases. A computer collects a temperature time series for a refrigeration case and, based on the temperature time series, learns a refrigeration case signature for both non-frost and defrost cycles. The computer generates features based on the refrigeration case signature and compares the refrigeration case signature to real time, or observed, temperatures and features using a rule-based and/or machine learning framework. Based on determining that the real time data varies beyond a threshold from the refrigeration case signature, the computer identifies a failure symptom of the refrigeration case and diagnoses a root cause of the symptom or failure. In addition, the computer may activate an alarm and open a work order corresponding to the root cause of the symptom or failure.

Abstract: A method, system, and computer program product to manage a network comprising a plurality of interconnected components are described. The method includes obtaining a set of all the components that are part of the network over time, and identifying one or more repeating patterns of components among the set of all the components as corresponding lower-level definitions to generate a hierarchical set of all the components. The method also includes obtaining time-varying information regarding topology and operational values within the network, and creating a representation of the network at a set of times based on the hierarchical set of all the components and the time-varying information.

Abstract: One embodiment provides a method, including: obtaining, at an information handling device, an image of a person; determining physical characteristics of the person by analyzing the image; receiving an image of at least one selected piece of jewelry, the selected jewelry having a given jewelry profile, wherein the jewelry profile describes features and construction of the selected piece of jewelry; overlaying the image of the at least one selected piece of jewelry onto an image of the person, wherein the overlaying comprises analyzing resizing the image of the at least one selected piece of jewelry to match the physical characteristics of the person, in view of the jewelry profile of the at least one selected piece of jewelry; and providing, on a display of the information handling device, an output image of the image of the person comprising the overlaid image of the at least one piece of jewelry.

Abstract: Methods, systems and computer program products for enhancing power outage recovery using a drone are provided. Aspects include identifying a predicted damage area based on one or more forecast models of a weather event and staging a drone in the predicted damage area prior to the weather event. Aspects also include dispatching the drone to survey one or more portions of the predicted damage area after the weather event and assessing damage to infrastructure equipment in the one or more portions of the predicted damage area. Aspects further include dispatching a repair crew based on the assessed damage.

Abstract: Methods, systems and computer program products for enhancing power outage recovery using a drone are provided. Aspects include identifying a predicted damage area based on one or more forecast models of a weather event and staging a drone in the predicted damage area prior to the weather event. Aspects also include dispatching the drone to survey one or more portions of the predicted damage area after the weather event and assessing damage to infrastructure equipment in the one or more portions of the predicted damage area. Aspects further include dispatching a repair crew based on the assessed damage.